Bargav Jayaraman and David Evans. Evaluating Differentially Private Machine Learning in Practice. 28th USENIX Security Symposium. Santa Clara. August 2019. [PDF, 20 pages] [arXiv] [code]
Bargav Jayaraman, Lingxiao Wang, David Evans and Quanquan Gu. Distributed Learning without Distress: Privacy-Preserving Empirical Risk Minimization. 32nd Conference on Neural Information Processing Systems (NeurIPS). Montreal, Canada. December 2018. [PDF, 19 pages, including supplemental materials]
Jack Doerner and abhi shelat. Scaling ORAM for Secure Computation. In 24th ACM Conference on Computer and Communications Security. Dallas, TX. 31 Oct-3 November 2017. (Best Paper Award)
Adrià Gascón and Phillipp Schoppmann and Borja Balle and Mariana Raykova and Jack Doerner and Samee Zahur and David Evans. Privacy-Preserving Distributed Linear Regression on High-Dimensional Data. In Privacy Enhancing Technologies Symposium (PETS). Minneapolis, Minnesota, 18 – 21 July 2017. [PDF]
Jack Doerner, David Evans, abhi shelat. Secure Stable Matching at Scale. In 23rd ACM Conference on Computer and Communications Security (CCS). Vienna, Austria. 24-28 October 2016. [PDF]
Samee Zahur, Xiao Wang, Mariana Raykova, Adrià Gascón, Jack Doerner, David Evans, Jonathan Katz. Revisiting Square-Root ORAM Efficient Random Access in Multi-Party Computation In 37th IEEE Symposium on Security and Privacy (“Oakland”). San Jose, CA. 23-25 May 2016. [PDF]
Samee Zahur, Mike Rosulek, and David Evans. Two Halves Make a Whole: Reducing Data Transfer in Garbled Circuits using Half Gates. In EuroCrypt 2015. Sofia, Bulgaria. 26-30 April 2015. [PDF, 28 pages] [Code]
Samee Zahur and David Evans. Obliv-C: A Language for Extensible Data-Oblivious Computation, Cryptology ePrint Archive: Report 2015:1153 [PDF], November 2015.
Samee Zahur and David Evans. Poster: Obliv-C: a Fast, Lightweight Language for Garbled Circuits. 36th IEEE Symposium on Security and Privacy (“Oakland”). 18-20 May 2015 (Poster).
Publications by Others using Obliv-C
Blind Justice: Fairness with Encrypted Sensitive Attributes. Niki Kilbertus, Adrià Gascón, Matt J. Kusner, Michael Veale, Krishna P. Gummadi, Adrian Weller. ICML 2018. PDF.
Private Nearest Neighbors Classification in Federated Databases, Phillipp Schoppmann, Adrià Gascón, and Borja Balle.
Cryptology ePrint Archive: Report 2018 / 289. March 2018.
Pretzel: Email encryption and provider-supplied functions are compatible, Trinabh Gupta, Henrique Fingler, Lorenzo Alvisi, and Michael Walfish. ACM SIGCOMM 2017.